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Article: Redesigning Banking PDF Table Extraction: A Layered Approach with Java
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In the complex world of banking, extracting data from PDF tables can pose significant challenges. Real bank statements are often messy, featuring scanned pages, shifting layouts, merged cells, and wrapped rows that can confound standard Java parsers. In this article, Mehuli Mukherjee presents a layered approach to redesigning PDF table extraction. By integrating stream parsing, lattice/OCR, validation, scoring, and selective machine learning, this innovative method enhances reliability in real banking systems, paving the way for more effective data management solutions.
PDF table extraction often looks easy until it fails in production. Real bank statements can be messy, with scanned pages, shifting layouts, merged cells, and wrapped rows that break standard Java parsers. This article shares how we redesigned the approach using stream parsing, lattice/OCR, validation, scoring, and selective ML to make extraction more reliable in real banking systems.
By Mehuli MukherjeeRead on the original site
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